google analytics website optimizer slideshare

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How to use web optimiser to test multiple designs and identify which is the best performing. The use of analytics and testing is a vital part of any web strategy and takes the guess work out of identifying design that will work for you.

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  • 1. Google Analytics and Website Optimizer Let your visitors lead you By Simon Whatley http://www.google.com/analytics http:// www.google.com/websiteoptimizer

2. Plan Measure Improve

  • Tactics without strategy are the noise before defeat
  • Sun Tzu, The Art of War.

3. Google Analytics http://www.google.com/analytics 4. Custom Dashboards 5. Topics to Cover

  • Profiles
  • Filters
  • Goals
  • Funnels

6. Profiles and Filters

  • The real strength of GA
  • Segment data
  • Deep analysis
  • Filter data depending on needs
  • Give access to data depending on needs
  • Starts collecting data once filter is applied
  • Best practice:
  • Profile with all data
  • Profile with segmented data

7. Profiles

  • Website URL
  • Profile Name
  • Time Zone
  • Default Page
  • Exclude Parameters
  • E-commerce Website
  • Search

8. Website Profiles

  • No Filters : Profile with zero filters. Use this for troubleshooting.
  • Only Direct : Include filter for the field "Campaign Source" only equaling the pattern "direct" visitors
  • Only Internal : Use an include filter which will include only traffic from internal IP ranges on IP address.
  • Only New Visitors : Include filter on the field "Visitor Type" equal to "new"
  • Only Organic : Include filter where the filter field is on "Campaign Medium" and the pattern is "organic"
  • Only Paid Search : Include filter on "Campaign Medium" equaling the pattern "ppc|cpc"
  • Only Referral : Include filter on "Campaign Medium" equaling "referral"
  • Only Returning Visitors : Include filter on "Visitor Type" equaling "returning"
  • Organic And Paid : Include filter combining the above two filters for "Only Organic" and "Only Paid Search" to include all search engine traffic
  • Overall : All traffic except filter out internal IP ranges using the " Exclude all traffic from an IP address filter ."

9. Filters

  • Applied to a Profile
  • Data Destructive change data forever!
  • Segmentation
  • Business rules
  • 2 types
    • Predefined
    • Custom
  • Filters data before submitting to GA database

10. Filters

  • Multiple Filters allowed
    • But, data output for filter 1 is data input for filter 2
  • Be careful! Filters are data destructive!
  • Avoid wrong conclusions!
    • Create multiple Profiles to prevent filter 1 impacting filter 2
  • Allows for customer segmentation
    • Visitor to member to customer

11. Pre-Defined Filters

  • Google Analytics provides you with three predefined filter types:
  • Exclude all traffic from a domain
  • Exclude all traffic from an IP address
  • Include only traffic to a subdirectory

12. Custom Filters

  • In addition, Google Analytics provides you with a number of custom options:
  • Exclude Pattern
  • Include Pattern
  • Search & Replace
  • Lookup Table
  • Advanced
  • Uppercase / Lowercase

13. Goals

  • Conversions?
    • Purchases
    • Registration
    • Send to a friend
    • Review or comment
    • Add to wish list
  • Maximum of 4 per profile

14. Funnels

  • Extension of Goals
  • Predefined steps
    • E.g. Purchase path from basket to confirmation
  • Track conversion process
    • See entry and exit points throughout process
  • Required steps?

15. Funnel Visualisation

  • Find out which pages result in lost conversions and where your would-be customers go.

16. E-commerce Tracking

  • vargaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www.");
  • document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));
  • varpageTracker = _gat._getTracker("UA-######-#");
  • pageTracker._trackPageview();
  • pageTracker._addTrans(
  • "1234",// Order ID
  • "Blah",// Affiliation
  • "100.00",// Total
  • "15.00",// Tax
  • "5",// Shipping
  • "Southwark",// City
  • "London",// State
  • "UK"// Country
  • );
  • pageTracker._addItem(
  • "1234",// Order ID
  • "DD44",// SKU
  • "Logo"// Product Name
  • "Design",// Category
  • "100.00",// Price
  • "1"// Quantity
  • );
  • pageTracker._trackTrans();
  • Trace transactions to campaigns and keywords, get loyalty and latency metrics, and identify your revenue sources.

17. Internal Site Search

  • Find out how your visitors search your site, what they look for, and where they end up.

18. Google Website Optimizer http:// www.google.com/websiteoptimizer 19. What to Test

  • Calls to action
  • Point of action assurances
  • Typography and colour
  • Product headlines, copy, images, descriptions
  • Category pages
  • About us, contact us, delivery, terms and conditions
  • Forms
  • Shopping carts
  • Offer incentives; etc

20. Page Priority Graph 21. Caveat

  • Website Optimizer tests can be used to testwhatpeople do, butnot whythey do it. You need to infer from the variations and the analytics and a good piece of market understanding (know thy customer).

22. Designing the Test

  • Before running the test, you must decide on these factors:
  • A control
  • A hypothesis
  • A time frame
  • A method of evaluating the results
  • During the tests, you cannot change your test, whatsoever!

23. Example Add to Cart Buttons

  • Variables
  • Shape, Size, Colour
  • Variations
  • Shape: Round, Square
  • Size: Small, Medium and Large
  • Colour: Red, Blue and Yellow
  • Hypotheses
  • Red buttons convert better than blue or yellow
  • Large buttons convert better than small or medium
  • Round buttons convert better than square

24. Website Optimizer Tests

  • Googles A/B test
  • Googles Multivariate test
  • Split-path test
  • Multipath Multivariate test
  • Do Anything test
  • Linger test
  • Click test

25. Design an A/B Test

  • Identify the metric.Whatare you going to compare and contrast?
  • Describe the metric.Howwill you compare and contrast the differences?
  • Optimise the system based on comparison of two or more tested solutions.

26. The Test Calculator

  • The number of combinations will affect how long you need to run a test to return meaningful results.
  • Factors:
  • Test combinations
  • Page views
  • % Visitors
  • Conversion rate
  • Expected Improvement

27. Example 1 (Not Recommended)

  • 1,000 test combinations
  • 10,000 page views per day
  • 100% visitors in experiment
  • 2.4% current conversion rate
  • 20% expected improvement (from 2.4% to 2.9%)
  • Duration of test: 3,515.9 days!

28. Example 2 (Recommended)

  • 20 test combinations
  • 10,000 page views per day
  • 100% visitors in experiment
  • 2.4% current conversion rate
  • 20% expected improvement (from 2.4% to 2.9%. Focusing on key elements in the combinations should increase expectations above this figure)
  • Duration of test: 37.8 days

29. The Test Setup

  • For a simple A/B Test, the following scripts are placed on the relevant pages.
  • Original Page
    • Control Script
    • Tracking Script
  • Variation Pages
    • Tracking Script
  • Conversion Page
    • C